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Victim Detection and Localization in Emergencies
Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658015/ https://www.ncbi.nlm.nih.gov/pubmed/36366134 http://dx.doi.org/10.3390/s22218433 |
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author | Álvarez-Merino, Carlos S. Khatib, Emil J. Luo-Chen, Hao Qiang Barco, Raquel |
author_facet | Álvarez-Merino, Carlos S. Khatib, Emil J. Luo-Chen, Hao Qiang Barco, Raquel |
author_sort | Álvarez-Merino, Carlos S. |
collection | PubMed |
description | Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victims in catastrophic scenarios. In this work, we present the benefits of using WiFi Fine Time Measurement (FTM), Ultra-Wide Band (UWB), and fusion technologies to locate victims under rubble. Integrating WiFi FTM and UWB in a drone may cover vast areas in a short time. Moreover, the detection capacity of WiFi and UWB for finding individuals is also compared. These findings are then used to propose a method for detecting and locating victims in disaster scenarios. |
format | Online Article Text |
id | pubmed-9658015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96580152022-11-15 Victim Detection and Localization in Emergencies Álvarez-Merino, Carlos S. Khatib, Emil J. Luo-Chen, Hao Qiang Barco, Raquel Sensors (Basel) Article Detecting and locating victims in emergency scenarios comprise one of the most powerful tools to save lives. Fast actions are crucial for victims because time is running against them. Radio devices are currently omnipresent within the physical proximity of most people and allow locating buried victims in catastrophic scenarios. In this work, we present the benefits of using WiFi Fine Time Measurement (FTM), Ultra-Wide Band (UWB), and fusion technologies to locate victims under rubble. Integrating WiFi FTM and UWB in a drone may cover vast areas in a short time. Moreover, the detection capacity of WiFi and UWB for finding individuals is also compared. These findings are then used to propose a method for detecting and locating victims in disaster scenarios. MDPI 2022-11-02 /pmc/articles/PMC9658015/ /pubmed/36366134 http://dx.doi.org/10.3390/s22218433 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Álvarez-Merino, Carlos S. Khatib, Emil J. Luo-Chen, Hao Qiang Barco, Raquel Victim Detection and Localization in Emergencies |
title | Victim Detection and Localization in Emergencies |
title_full | Victim Detection and Localization in Emergencies |
title_fullStr | Victim Detection and Localization in Emergencies |
title_full_unstemmed | Victim Detection and Localization in Emergencies |
title_short | Victim Detection and Localization in Emergencies |
title_sort | victim detection and localization in emergencies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658015/ https://www.ncbi.nlm.nih.gov/pubmed/36366134 http://dx.doi.org/10.3390/s22218433 |
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